C-center preprocessing
1 Data check
1.1 Load packages
library("dplyr")##
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## intersect, setdiff, setequal, unionlibrary("tidyr")
library("ggplot2")
library("stringr")
library("tigerstats")## Loading required package: abd## Loading required package: nlme##
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## cooks.distance.influence.merMod car
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## dfbetas.influence.merMod car1.2 Read data
df <- read.csv("../data/c-center_16th_Sep.csv", header = TRUE, sep = ",")
load("../data/speech_rate.Rda")1.3 Merge mview output with speech rate dataframe
df <- df %>%
right_join(df_sr, by=c("subj", "fname"))
rm(df_sr)1.4 Tidy the data
# extract info from filename, merge trialnumber and repetition
df<- df %>%
separate(fname, c("project", "prompt", "block", "remove", "remove2", "trialno", "repetition"), sep = "_") %>%
mutate(trial=str_c(trialno,repetition)) Drop unwanted columns.
df <- df %>%
select(-c(project, remove, remove2, x1, x2, x3, x4, x5, x6, x7, y1, y2, y3, y4, y5, y6, y7, z1, z2, z3, z4, z5, z6, z7, v1, v2, v3, v4, v5, v6, v7, X.1, X.2, X.3, DOns, DTarg, DOff))Create new variable recording.no to indicate the recording number (first recording, second recording etc..).
trialno <- df %>%
group_by(subj) %>%
distinct(trial) %>%
arrange(trial, by_group = TRUE) %>%
mutate(recording.no = 1:n()) %>%
select(recording.no, everything()) %>%
arrange(subj, recording.no)Bind trialno with dataframe.
df <- df %>%
inner_join(trialno, by = c("subj", "trial")) %>%
select(recording.no, everything()) %>%
arrange(subj, recording.no)
rm(trialno)Create group variable.
df$group <- ifelse((str_detect(df$subj, "CTRL")), "CTRL", "PD")
df$group <- as.factor(df$group)Create condition based on prompt.
df$condition <- "C"
df$condition[df$prompt == "oma spat" | df$prompt == "opa Smat" |df$prompt == "opa schat" | df$prompt == "oma's prak"] <- "CC"
df$condition[df$prompt == "oma sprak"] <- "CCC"
df$condition <- as.factor(df$condition)Create cluster column.
df$cluster[df$prompt == "oma spat" | df$prompt == "oma's pad"] <- "sp"
df$cluster[df$prompt == "opa schat" | df$prompt == "opa's gat"] <- "sx"
df$cluster[df$prompt == "opa Smat" | df$prompt == "opa's mat"] <- "sm"
df$cluster[df$prompt == "oma sprak" | df$prompt == "oma's prak"] <- "spr"
df$cluster <- as.factor(df$cluster)
levels(df$cluster)## [1] "sm" "sp" "spr" "sx"Remove faulty segmentation, based on outlier column.
df <- df[is.na(df$outl),]Check whether the conditions are well coded and whether the segmentation involves the correct articulators.
table(df$prompt, df$condition)##
## C CC CCC
## oma spat 0 1814 0
## oma sprak 0 0 1677
## oma's pad 1797 0 0
## oma's prak 0 1704 0
## opa schat 0 1695 0
## opa Smat 0 1789 0
## opa's gat 1697 0 0
## opa's mat 1762 0 0table(df$prompt, df$cluster)##
## sm sp spr sx
## oma spat 0 1814 0 0
## oma sprak 0 0 1677 0
## oma's pad 0 1797 0 0
## oma's prak 0 0 1704 0
## opa schat 0 0 0 1695
## opa Smat 1789 0 0 0
## opa's gat 0 0 0 1697
## opa's mat 1762 0 0 0table(df$seg, df$traj)##
## LA TB_X TB_XZ TB_Z TT_X TT_XZ TT_Z
## É‘ 93 0 59 2154 332 0 0 0
## k 44 0 0 159 683 0 0 0
## m 23 869 0 0 0 0 0 0
## p 52 1749 0 0 0 0 0 0
## r 79 0 18 54 31 0 285 262
## s 109 0 0 0 0 0 3357 60
## t 67 0 0 0 0 58 2349 207
## X 37 0 142 298 305 0 0 0Remove unreliable /sx/ segmentation of PD25.
df <- df[!(df$subj == "PD25" & df$cluster == "sx"),]2 Preparing data for within cluster analysis
/sp/ CC lag
# collect offset times /s/
offset.s <- df %>%
rowwise() %>%
filter(prompt == "oma spat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
select(subj, recording.no, t3, t5) %>%
rename(t3.s = t3) %>%
rename(t5.s = t5)
# collect onset times /p/ and merge df's
sp.CC <- df %>%
rowwise() %>%
filter(prompt == "oma spat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
select(subj, recording.no, prompt, block, condition, group, cluster, duration.tt, duration.mt, t3, t5) %>%
rename(t3.p = t3) %>%
rename(t5.p = t5) %>%
inner_join(offset.s, by=c("subj", "recording.no")) %>%
mutate(time.lag = t3.p-t5.s) %>%
mutate(time.lag.norm = time.lag/(t5.p - t3.s)) %>%
mutate(dur.C1.norm = (t5.s - t3.s)/(t5.p - t3.s)) %>%
mutate(dur.C2.norm = (t5.p - t3.p)/(t5.p - t3.s))
plot(sp.CC$time.lag.norm, sp.CC$dur.C2.norm)
cor(sp.CC$time.lag.norm, sp.CC$dur.C2.norm, use = "complete.obs")## [1] -0.4257756plot(sp.CC$time.lag.norm[sp.CC$group == "CTRL"], sp.CC$dur.C1.norm[sp.CC$group == "CTRL"])
plot(sp.CC$time.lag.norm[sp.CC$group == "PD"], sp.CC$dur.C1.norm[sp.CC$group == "PD"])
rm(offset.s)
# getting rid of NA's
sp.CC <- na.omit(sp.CC, cols="time.lag.norm")
# plot
ggplot(sp.CC, aes(x=subj, y=time.lag.norm, fill=group, na.rm = T)) + geom_boxplot() + labs(title = "CTRL: /sp/", y = "Lag between C's")
/sm/ CC lag
# collect offset times /s/
offset.s <- df %>%
rowwise() %>%
filter(prompt == "opa Smat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
select(subj, recording.no, t3, t5) %>%
rename(t5.s = t5, t3.s = t3)
# collect offset times /m/
sm.CC <- df %>%
rowwise() %>%
filter(prompt == "opa Smat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "m") %>%
select(subj, recording.no, prompt, block, condition, group, cluster, duration.tt, duration.mt, t3, t5) %>%
rename(t3.m = t3, t5.m = t5) %>%
inner_join(offset.s, by=c("subj", "recording.no")) %>%
mutate(time.lag = t3.m-t5.s) %>%
mutate(time.lag.norm = time.lag/(t5.m - t3.s)) %>%
mutate(dur.C1.norm = (t5.s - t3.s)/(t5.m - t3.s)) %>%
mutate(dur.C2.norm = (t5.m - t3.m)/(t5.m - t3.s))
plot(sm.CC$time.lag.norm, sm.CC$dur.C2.norm)
cor(sm.CC$time.lag.norm, sm.CC$dur.C2.norm, use = "complete.obs")## [1] -0.1151117plot(sm.CC$time.lag.norm[sm.CC$group == "CTRL"], sm.CC$dur.C1.norm[sm.CC$group == "CTRL"], use = "complete.obs")## Warning in plot.window(...): "use" is not a graphical parameter## Warning in plot.xy(xy, type, ...): "use" is not a graphical parameter## Warning in axis(side = side, at = at, labels = labels, ...): "use" is not a
## graphical parameter
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## graphical parameter## Warning in box(...): "use" is not a graphical parameter## Warning in title(...): "use" is not a graphical parameter
plot(sm.CC$time.lag.norm[sm.CC$group == "PD"], sm.CC$dur.C1.norm[sm.CC$group == "PD"], use = "complete.obs")## Warning in plot.window(...): "use" is not a graphical parameter## Warning in plot.xy(xy, type, ...): "use" is not a graphical parameter## Warning in axis(side = side, at = at, labels = labels, ...): "use" is not a
## graphical parameter
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## graphical parameter## Warning in box(...): "use" is not a graphical parameter## Warning in title(...): "use" is not a graphical parameter
rm(offset.s)
# getting rid of NA's
sm.CC <- na.omit(sm.CC, cols="time.lag.norm")
# plot
ggplot(sm.CC, aes(x=subj, y=time.lag.norm, fill=group, na.rm = T)) + geom_boxplot() + labs(title = "PD: /sm/", y = "Lag between C's (ms)")
/sx/ CC lag
# collect offset times /s/
offset.s <- df %>%
rowwise() %>%
filter(prompt == "opa schat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
select(subj, recording.no, t3, t5) %>%
rename(t3.s = t3, t5.s = t5)
# collect onset times /x/
sx.CC <- df %>%
rowwise() %>%
filter(prompt == "opa schat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "X") %>%
select(subj, recording.no, prompt, block, condition, group, cluster, duration.tt, duration.mt, t3, t5) %>%
rename(t3.x = t3, t5.x = t5) %>%
inner_join(offset.s, by=c("subj", "recording.no")) %>%
mutate(time.lag = t3.x-t5.s) %>%
mutate(time.lag.norm = time.lag/(t5.x - t3.s)) %>%
mutate(dur.C1.norm = (t5.s - t3.s)/(t5.x - t3.s)) %>%
mutate(dur.C2.norm = (t5.x - t3.x)/(t5.x - t3.s))
plot(sx.CC$time.lag.norm, sx.CC$dur.C2.norm)
cor(sx.CC$time.lag.norm, sx.CC$dur.C2.norm, use = "complete.obs")## [1] -0.9249422plot(sx.CC$time.lag.norm[sx.CC$group == "CTRL"], sx.CC$dur.C1.norm[sx.CC$group == "CTRL"])
plot(sx.CC$time.lag.norm[sx.CC$group == "PD"], sx.CC$dur.C1.norm[sx.CC$group == "PD"])
# getting rid of NA's
sx.CC <- na.omit(sx.CC, cols="time.lag.norm")
# plot
ggplot(sx.CC, aes(x=subj, y=time.lag.norm, fill=group, na.rm = T)) + geom_boxplot() + labs(title = "PD: /sx/", y = "Lag between C's (ms)")
/s-r/ CC lag
# collect on and offset times /s/
offset.s <- df %>%
rowwise() %>%
filter(prompt == "oma's prak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
select(subj, recording.no, t3, t5) %>%
rename(t3.s = t3, t5.s = t5)
# collect on and offset times /p/
offset.p <- df %>%
rowwise() %>%
filter(prompt == "oma's prak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
select(subj, recording.no, t3, t5) %>%
rename(t3.p = t3, t5.p = t5)
# collect on and offset times /r/
spr.CC <- df %>%
rowwise() %>%
filter(prompt == "oma's prak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "r") %>%
select(subj, recording.no, prompt, block, condition, group, cluster, duration.tt, duration.mt, t3, t5) %>%
rename(t3.r = t3, t5.r = t5) %>%
inner_join(offset.s, by=c("subj", "recording.no")) %>%
left_join(offset.p, by=c("subj", "recording.no")) %>%
mutate(time.lag = t3.r-t5.s) %>%
mutate(time.lag.norm = time.lag/(t5.r - t3.s)) %>%
mutate(dur.C1.norm = (t5.s - t3.s)/(t5.r - t3.s)) %>%
mutate(dur.C2.norm = (t5.p - t3.p)/(t5.r - t3.s)) %>%
mutate(dur.C3.norm = (t5.r - t3.r)/(t5.r - t3.s))
plot(spr.CC$time.lag.norm, spr.CC$dur.C2.norm)
cor(spr.CC$time.lag.norm, spr.CC$dur.C2.norm, use = "complete.obs") ## [1] 0.1506096plot(spr.CC$time.lag.norm, spr.CC$dur.C3.norm)
cor(spr.CC$time.lag.norm, spr.CC$dur.C3.norm, use = "complete.obs")## [1] -0.48932cor(spr.CC$time.lag.norm[spr.CC$group == "CTRL"], spr.CC$dur.C1.norm[spr.CC$group == "CTRL"])## [1] NAcor(spr.CC$time.lag.norm[spr.CC$group == "PD"], spr.CC$dur.C1.norm[spr.CC$group == "PD"])## [1] NAplot(spr.CC$time.lag.norm[spr.CC$group == "CTRL"], spr.CC$dur.C1.norm[spr.CC$group == "CTRL"])
plot(spr.CC$time.lag.norm[spr.CC$group == "PD"], spr.CC$dur.C1.norm[spr.CC$group == "PD"])
rm(offset.s)
# getting rid of NA's
spr.CC <- na.omit(spr.CC, cols="time.lag.norm")
# plot
ggplot(spr.CC, aes(x=subj, y=time.lag.norm, fill=group, na.rm = T)) + geom_boxplot() + labs(title = "PD: /spr/", y = "Lag between /s/ and /r/ (ms)")
Merge.
df.CC.lag<- rbind(sm.CC, sp.CC, sx.CC, spr.CC)
rm(sm.CC, sp.CC, sx.CC, spr.CC)2.1 Some plots
dodge <- position_dodge(width = 0.9)
ggplot(df.CC.lag, aes(x=condition, y=time.lag, fill=group)) + geom_violin() + labs(title = "CC lag all clusters", y = "Lag between C's") + geom_boxplot(width=.2, position = dodge)
ggplot(df.CC.lag[df.CC.lag$cluster == "sp",], aes(x=condition, y=time.lag.norm, fill=group)) + geom_violin() + labs(title = "CC lag /sp/", y = "Lag between C's") + geom_boxplot(width=.2, position = dodge)
ggplot(df.CC.lag[df.CC.lag$cluster == "sm",], aes(x=condition, y=time.lag.norm, fill=group)) + geom_violin() + labs(title = "CC lag /sm/", y = "Lag between C's") + geom_boxplot(width=.2, position = dodge)
ggplot(df.CC.lag[df.CC.lag$cluster == "sx",], aes(x=condition, y=time.lag.norm, fill=group)) + geom_violin() + labs(title = "CC lag /sx/", y = "Lag between C's") + geom_boxplot(width=.2, position = dodge)
ggplot(df.CC.lag[df.CC.lag$cluster == "spr",], aes(x=condition, y=time.lag.norm, fill=group)) + geom_violin() + labs(title = "CC lag /spr/", y = "Lag between /s/ and /r/") + geom_boxplot(width=.2, position = dodge)
3 Examining duration of C’s in onset.
df <- df %>%
rowwise() %>%
mutate(dur=t5 - t3) %>%
group_by(subj, cluster, seg) %>%
mutate(norm.dur = scale(dur))
mean.dur.C <- df %>%
group_by(cluster, condition, subj) %>%
filter(condition == "C") %>%
filter(seg == "p"| seg == "m" | seg == "X") %>%
group_by(seg) %>%
select(cluster, condition, subj, seg, dur) %>%
mutate(mean.dur.C = mean(dur, na.rm=T)) %>%
distinct(subj, seg, mean.dur.C)
diff <- df %>%
group_by(cluster, condition, subj) %>%
filter(condition == "CC") %>%
filter(seg == "p"| seg == "m" | seg == "X") %>%
group_by(seg, subj) %>%
select(cluster, condition, subj, seg, dur) %>%
mutate(mean.dur.CC = mean(dur, na.rm=T)) %>%
distinct(subj, seg, mean.dur.CC) %>%
inner_join(mean.dur.C, by=c("subj", "seg")) %>%
mutate(diff = mean.dur.C - mean.dur.CC)
diff %>%
group_by(seg) %>%
summarize(mean = mean(diff, na.rm=T), sd = sd(diff, na.rm=T))## `summarise()` ungrouping output (override with `.groups` argument)Plot durations of right C per group:
require(gridExtra)## Loading required package: gridExtra##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
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## combineplot1 <- ggplot(df[df$cluster == 'sp' & df$seg == "p",], aes(x=group, y=norm.dur, fill=condition)) + labs(title = "Duration /p/", y = "Duration (ms)", x = "Group") + geom_boxplot(width=.2, position = dodge)
plot2 <- ggplot(df[df$cluster == 'sm' & df$seg == "m",], aes(x=group, y=norm.dur, fill=condition)) + labs(title = "Duration /m/", y = "Duration (ms)", x = "Group") + geom_boxplot(width=.2, position = dodge)
plot3 <- ggplot(df[df$cluster == 'sx' & df$seg == "X",], aes(x=group, y=norm.dur, fill=condition)) + labs(title = "Duration /x/", y = "Duration (ms)", x = "Group") + geom_boxplot(width=.2, position = dodge)
plot4 <- ggplot(df[df$cluster == 'spr' & df$seg == "r",], aes(x=group, y=norm.dur, fill=condition)) + labs(title = "Duration /r/", y = "Duration (ms)", x = "Group") + geom_boxplot(width=.2, position = dodge)
grid.arrange(plot1, plot2, plot3, plot4, ncol=2)## Warning: Removed 14 rows containing non-finite values (stat_boxplot).## Warning: Removed 28 rows containing non-finite values (stat_boxplot).## Warning: Removed 49 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
rm(plot1, plot2, plot3, plot4)Plot durations of right C per subject:
ggplot(df[df$cluster == 'sm' & df$seg == "m" & df$group == "CTRL",], aes(x=subj, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /m/ CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 8 rows containing non-finite values (stat_ydensity).## Warning: Removed 8 rows containing non-finite values (stat_boxplot).
ggplot(df[df$cluster == 'sm' & df$seg == "m" & df$group == "PD",], aes(x=subj, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /m/ PD", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 20 rows containing non-finite values (stat_ydensity).## Warning: Removed 20 rows containing non-finite values (stat_boxplot).
ggplot(df[df$cluster == 'sp' & df$seg == "p" & df$group == "CTRL",], aes(x=subj, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /p/ CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 12 rows containing non-finite values (stat_ydensity).## Warning: Removed 12 rows containing non-finite values (stat_boxplot).
ggplot(df[df$cluster == 'sp' & df$seg == "p" & df$group == "PD",], aes(x=subj, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /p/ PD", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 4 rows containing non-finite values (stat_ydensity).## Warning: Removed 4 rows containing non-finite values (stat_boxplot).
Plot duration of first C per group
ggplot(df[df$cluster == 'sm' & df$seg == "s",], aes(x=group, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /s/ in /sm/ and /s#m/", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 29 rows containing non-finite values (stat_ydensity).## Warning: Removed 29 rows containing non-finite values (stat_boxplot).
ggplot(df[df$cluster == 'sp' & df$seg == "s",], aes(x=group, y=dur, fill=condition)) + geom_violin() + labs(title = "duration /s/ in /sp/ and /s#p/", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 15 rows containing non-finite values (stat_ydensity).## Warning: Removed 15 rows containing non-finite values (stat_boxplot).
Compare duration of C’s in onset per group
ggplot(df[df$cluster == 'sm' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=group, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and /m/ in CC, CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 40 rows containing non-finite values (stat_ydensity).## Warning: Removed 40 rows containing non-finite values (stat_boxplot).
ggplot(df[df$cluster == 'sp' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=group, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and /p/ in CC, CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 17 rows containing non-finite values (stat_ydensity).## Warning: Removed 17 rows containing non-finite values (stat_boxplot).
Compare duration of C’s in onset per subj
ggplot(df[df$group == 'CTRL' & df$cluster == 'sm' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=subj, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and/m/ in CC, CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 8 rows containing non-finite values (stat_ydensity).## Warning: Removed 8 rows containing non-finite values (stat_boxplot).
ggplot(df[df$group == 'PD' & df$cluster == 'sm' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=subj, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and/m/ in CC, PD", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 32 rows containing non-finite values (stat_ydensity).## Warning: Removed 32 rows containing non-finite values (stat_boxplot).
ggplot(df[df$group == 'CTRL' & df$cluster == 'sp' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=subj, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and/p/ in CC, CTRL", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 13 rows containing non-finite values (stat_ydensity).## Warning: Removed 13 rows containing non-finite values (stat_boxplot).
ggplot(df[df$group == 'PD' & df$cluster == 'sp' & df$seg != "É‘" & df$seg != "t" & df$condition == "CC",], aes(x=subj, y=dur, fill=seg)) + geom_violin() + labs(title = "duration /s/ and /p/ in CC, PD", y = "duration") + geom_boxplot(width=.2, position = dodge) + ylim(0, 300)## Warning: Removed 4 rows containing non-finite values (stat_ydensity).## Warning: Removed 4 rows containing non-finite values (stat_boxplot).
## Density plots duration
ggplot(df[df$cluster == 'sp' & df$seg == "p" & df$group == "CTRL",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /p/, CTRL") + xlim(0, 200)## Warning: Removed 14 rows containing non-finite values (stat_density).
ggplot(df[df$cluster == 'sp' & df$seg == "p" & df$group == "PD",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /p/, PD") + xlim(0, 200)## Warning: Removed 5 rows containing non-finite values (stat_density).
ggplot(df[df$cluster == 'sm' & df$seg == "m" & df$group == "CTRL",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /m/, CTRL") + xlim(0, 200)## Warning: Removed 10 rows containing non-finite values (stat_density).
ggplot(df[df$cluster == 'sm' & df$seg == "m" & df$group == "PD",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /m/, PD") + xlim(0, 200)## Warning: Removed 21 rows containing non-finite values (stat_density).
ggplot(df[df$cluster == 'sx' & df$seg == "X" & df$group == "CTRL",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /x/, CTRL") + xlim(0, 200)## Warning: Removed 41 rows containing non-finite values (stat_density).
ggplot(df[df$cluster == 'sx' & df$seg == "X" & df$group == "PD",], aes(x=dur, fill = condition)) +
geom_density(alpha=0.4) + ggtitle("Distribution duration /x/, PD") + xlim(0, 200)## Warning: Removed 14 rows containing non-finite values (stat_density).
4 Examining landmarks
4.1 Derive temporal midpoint of nucleus
df <- df %>%
rowwise() %>%
mutate(mid.nuc=mean(c(t3, t5), na.rm=T)) 4.2 Examine relation gestural onset/offest to nucleus midpoint
df.density <- df %>%
rowwise() %>%
mutate(GONS = mid.nuc - t1) %>%
mutate(GOFF = t7 - mid.nuc) %>%
gather(side, time.to.mid, GONS:GOFF, factor_key=TRUE, na.rm = T)
ggplot(df.density[df.density$condition == 'C' & df.density$seg == "s",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /s/ in C")
ggplot(df.density[df.density$condition == 'CC' & df.density$seg == "s",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /s/ in CC")
ggplot(df.density[df.density$condition == 'C' & df.density$seg == "m",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /m/ in C")
ggplot(df.density[df.density$condition == 'CC' & df.density$seg == "m",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /m/ in CC")
ggplot(df.density[df.density$condition == 'C' & df.density$seg == "p",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /p/ in C")
ggplot(df.density[df.density$condition == 'CC' & df.density$seg == "p",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /p/ in CC")
ggplot(df.density[df.density$condition == 'C' & df.density$seg == "X",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /x/ in C")
ggplot(df.density[df.density$condition == 'CC' & df.density$seg == "X",], aes(x=time.to.mid, fill = side)) +
geom_density(alpha=0.4) + ggtitle("Distribution time to midpoint /x/ in CC")
5 Preparing data for C-center analysis based on nucleus on and offset
5.1 Calculate lag’s for /sp/
# derive time of nucleus midpoint onset /p/
mid.nuc.p <- df %>%
filter(prompt == "oma spat" | prompt == "oma's pad" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
rename(mid.nuc.p = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.p)
# derive time of nucleus midpoint onset /s/
mid.nuc.s <- df %>%
filter(prompt == "oma spat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(mid.nuc.s = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.s)
# calculate C-center
sp.c.center <- mid.nuc.p %>%
filter(prompt == "oma spat" | prompt == "oma's pad" ) %>%
left_join(mid.nuc.s, by=c("subj", "prompt", "recording.no")) %>%
rowwise() %>%
mutate(c.center = case_when(prompt == "oma's pad" ~ mid.nuc.p, prompt == "oma spat" ~ mean(c(mid.nuc.s, mid.nuc.p)))) %>%
select(subj, recording.no, c.center)
rm(mid.nuc.p, mid.nuc.s)Get rightedge /sp/
# collect offset times /p/
sp.rightedge <- df %>%
filter(prompt == "oma spat" | prompt == "oma's pad" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
rename(rightedge = t5) %>%
select(subj, recording.no, rightedge) Get leftedge /sp/
# collect onset times /s/
sp.leftedge.CC <- df %>%
filter(prompt == "oma spat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Get leftedge /p/
# collect offset times /p/
sp.leftedge.C <- df %>%
filter(prompt == "oma's pad") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Merge
sp.leftedge <- rbind(sp.leftedge.CC, sp.leftedge.C)Get anchor /t/
# collect onset times coda /t/
sp.anchor <- df %>%
filter(prompt == "oma spat" | prompt == "oma's pad" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "t") %>%
rename(anchor = t3) %>%
select(subj, recording.no, anchor) Merge and remove obsolete df’s
df.C.center.sp <- df %>%
filter(prompt == "oma spat" | prompt == "oma's pad" ) %>%
left_join(sp.c.center, by =c("subj", "recording.no")) %>%
left_join(sp.rightedge, by =c("subj", "recording.no")) %>%
left_join(sp.leftedge, by =c("subj", "recording.no")) %>%
left_join(sp.anchor, by =c("subj", "recording.no"))
rm(sp.c.center, sp.rightedge, sp.anchor)5.2 Calculate lag’s for /sm/
# collect mid.nuc time onset /m/
mid.nuc.m <- df %>%
filter(prompt == "opa Smat" | prompt == "opa's mat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "m") %>%
rename(mid.nuc.m = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.m)
# collect mid.nuc time onset /s/
mid.nuc.s <- df %>%
filter(prompt == "opa Smat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(mid.nuc.s = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.s)
# calculate C-center
sm.c.center <- mid.nuc.m %>%
filter(prompt == "opa Smat" | prompt == "opa's mat" ) %>%
left_join(mid.nuc.s, by=c("subj", "prompt", "recording.no")) %>%
rowwise() %>%
mutate(c.center = case_when(prompt == "opa's mat" ~ mid.nuc.m, prompt == "opa Smat" ~ mean(c(mid.nuc.s, mid.nuc.m)))) %>%
select(subj, recording.no, c.center)
rm(mid.nuc.m, mid.nuc.s)Get rightedge /sm/
# collect offset times /m/
sm.rightedge <- df %>%
filter(prompt == "opa Smat" | prompt == "opa's mat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "m") %>%
rename(rightedge = t5) %>%
select(subj, recording.no, rightedge) Get leftedge /sm/
# collect onset times /s/
sm.leftedge.CC <- df %>%
filter(prompt == "opa Smat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Get leftedge /m/
# collect onset times /m/
sm.leftedge.C <- df %>%
filter(prompt == "opa's mat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "m") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Merge
sm.leftedge <- rbind(sm.leftedge.CC, sm.leftedge.C)Get anchor /t/
# collect onset times coda /t/
sm.anchor <- df %>%
filter(prompt == "opa Smat" | prompt == "opa's mat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "t") %>%
rename(anchor = t3) %>%
select(subj, recording.no, anchor) Merge and remove obsolete df’s
df.C.center.sm <- df %>%
filter(prompt == "opa Smat" | prompt == "opa's mat" ) %>%
left_join(sm.c.center, by =c("subj", "recording.no")) %>%
left_join(sm.rightedge, by =c("subj", "recording.no")) %>%
left_join(sm.leftedge, by =c("subj", "recording.no")) %>%
left_join(sm.anchor, by =c("subj", "recording.no"))
rm(sm.c.center, sm.rightedge, sm.anchor)5.3 Calculate lag’s for /sx/
# collect mid.nuc time onset /x/
mid.nuc.x <- df %>%
filter(prompt == "opa schat" | prompt == "opa's gat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "X") %>%
rename(mid.nuc.x = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.x)
# collect mid.nuc time onset /s/
mid.nuc.s <- df %>%
filter(prompt == "opa schat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(mid.nuc.s = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.s)
# calculate C-center
sx.c.center <- mid.nuc.x %>%
filter(prompt == "opa schat" | prompt == "opa's gat" ) %>%
left_join(mid.nuc.s, by=c("subj", "prompt", "recording.no")) %>%
rowwise() %>%
mutate(c.center = case_when(prompt == "opa's gat" ~ mid.nuc.x, prompt == "opa schat" ~ mean(c(mid.nuc.s, mid.nuc.x)))) %>%
select(subj, recording.no, c.center)
rm(mid.nuc.x, mid.nuc.s)Get rightedge /sx/
# collect offset times /x/
sx.rightedge <- df %>%
filter(prompt == "opa schat" | prompt == "opa's gat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "X") %>%
rename(rightedge = t5) %>%
select(subj, recording.no, rightedge) Get leftedge /sx/
# collect onset times /s/
sx.leftedge.CC <- df %>%
filter(prompt == "opa schat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Get leftedge /x/
# collect onset times /m/
sx.leftedge.C <- df %>%
filter(prompt == "opa's gat") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "X") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Merge
sx.leftedge <- rbind(sx.leftedge.CC, sx.leftedge.C)Get anchor /t/
# collect onset times coda /t/
sx.anchor <- df %>%
filter(prompt == "opa schat" | prompt == "opa's gat" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "t") %>%
rename(anchor = t3) %>%
select(subj, recording.no, anchor) Merge and remove obsolete df’s
df.C.center.sx <- df %>%
filter(prompt == "opa schat" | prompt == "opa's gat" ) %>%
left_join(sx.c.center, by =c("subj", "recording.no")) %>%
left_join(sx.rightedge, by =c("subj", "recording.no")) %>%
left_join(sx.leftedge, by =c("subj", "recording.no")) %>%
left_join(sx.anchor, by =c("subj", "recording.no"))
rm(sx.c.center, sx.rightedge, sx.anchor)5.4 Calculate lag’s for /spr/
# collect mid.nuc time onset /r/
mid.nuc.r <- df %>%
filter(prompt == "oma sprak" | prompt == "oma's prak" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "r") %>%
rename(mid.nuc.r = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.r)
# collect mid.nuc time onset /p/
mid.nuc.p <- df %>%
filter(prompt == "oma sprak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
rename(mid.nuc.p = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.p)
# collect mid.nuc time onset /s/
mid.nuc.s <- df %>%
filter(prompt == "oma sprak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(mid.nuc.s = mid.nuc) %>%
select(subj, prompt, recording.no, mid.nuc.s)
# calculate C-center
spr.c.center <- mid.nuc.r %>%
filter(prompt == "oma sprak" | prompt == "oma's prak" ) %>%
left_join(mid.nuc.s, by=c("subj", "prompt", "recording.no")) %>%
left_join(mid.nuc.p, by=c("subj", "prompt", "recording.no")) %>%
rowwise() %>%
mutate(c.center = case_when(prompt == "oma's prak" ~ mid.nuc.r, prompt == "oma sprak" ~ mean(c(mid.nuc.s, mid.nuc.p, mid.nuc.r)))) %>%
select(subj, recording.no, c.center)
rm(mid.nuc.r, mid.nuc.s, mid.nuc.p)Get rightedge /spr/
# collect offset times /r/
spr.rightedge <- df %>%
filter(prompt == "oma sprak" | prompt == "oma's prak" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "r") %>%
rename(rightedge = t5) %>%
select(subj, recording.no, rightedge) Get leftedge /spr/
# collect onset times /s/
spr.leftedge.CCC <- df %>%
filter(prompt == "oma sprak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "s") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Get leftedge /pr/
# collect onset times /p/
spr.leftedge.CC <- df %>%
filter(prompt == "oma's prak") %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "p") %>%
rename(leftedge = t3) %>%
select(subj, recording.no, leftedge) Merge
spr.leftedge <- rbind(spr.leftedge.CCC, spr.leftedge.CC)Get anchor /k/
# collect onset times coda /t/
spr.anchor <- df %>%
filter(prompt == "oma sprak" | prompt == "oma's prak" ) %>%
group_by(subj) %>%
group_by(recording.no) %>%
filter(seg == "k") %>%
rename(anchor = t3) %>%
select(subj, recording.no, anchor) Merge and remove obsolete df’s
df.C.center.spr <- df %>%
filter(prompt == "oma sprak" | prompt == "oma's prak" ) %>%
left_join(spr.c.center, by =c("subj", "recording.no")) %>%
left_join(spr.rightedge, by =c("subj", "recording.no")) %>%
left_join(spr.leftedge, by =c("subj", "recording.no")) %>%
left_join(spr.anchor, by =c("subj", "recording.no"))
rm(spr.c.center, spr.rightedge, spr.anchor)5.5 Merge C-center df’s
df.C.center <- rbind(df.C.center.sp, df.C.center.sm, df.C.center.sx, df.C.center.spr)
rm(df.C.center.sp, df.C.center.sm, df.C.center.sx, df.C.center.spr)
df.C.center <- df.C.center %>%
rowwise() %>%
mutate(c.center.lag = anchor - c.center) %>%
mutate(rightedge.lag = anchor - rightedge)%>%
mutate(leftedge.lag = anchor - leftedge) 5.6 Distribution
xtabs(c.center.lag ~ subj, data = df.C.center)## subj
## CTRL01 CTRL02 CTRL03 CTRL04 CTRL05 CTRL06 CTRL07 CTRL08
## 68346.38 67985.00 66015.00 39041.67 61045.21 77442.77 59773.33 64839.58
## CTRL09 CTRL10 CTRL11 CTRL12 CTRL13 CTRL14 CTRL15 CTRL16
## 52433.75 64502.50 87568.75 64269.17 47137.50 66209.38 61985.83 40075.00
## CTRL17 CTRL18 CTRL19 CTRL20 CTRL21 CTRL23 CTRL24 CTRL25
## 34172.50 56182.92 24673.33 44129.38 67449.17 54278.33 43338.33 55485.00
## PD01 PD02 PD03 PD04 PD05 PD06 PD07 PD08
## 45974.17 55416.25 46407.50 38454.17 59822.90 57576.25 52457.50 51268.75
## PD09 PD10 PD11 PD12 PD13 PD14 PD15 PD16
## 61385.00 59955.00 53438.70 50727.50 66320.67 57586.25 59913.33 49079.17
## PD17 PD18 PD19 PD21 PD22 PD23 PD25
## 60586.04 60655.42 9437.50 51785.83 49108.12 29948.33 37824.17 0.005.7 Some plots
5.7.1 Per group
/sm/
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, c-center", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 198 rows containing non-finite values (stat_ydensity).## Warning: Removed 198 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, rightedge", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 158 rows containing non-finite values (stat_ydensity).## Warning: Removed 158 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, leftedge", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 563 rows containing non-finite values (stat_ydensity).## Warning: Removed 563 rows containing non-finite values (stat_boxplot).
/sp/
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, c-center", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 160 rows containing non-finite values (stat_ydensity).## Warning: Removed 160 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 104 rows containing non-finite values (stat_ydensity).## Warning: Removed 104 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 516 rows containing non-finite values (stat_ydensity).## Warning: Removed 516 rows containing non-finite values (stat_boxplot).
/sx/
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, c-center", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 558 rows containing non-finite values (stat_ydensity).## Warning: Removed 558 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 531 rows containing non-finite values (stat_ydensity).## Warning: Removed 531 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 604 rows containing non-finite values (stat_ydensity).## Warning: Removed 604 rows containing non-finite values (stat_boxplot).
/spr/
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, c-center", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1156 rows containing non-finite values (stat_ydensity).## Warning: Removed 1156 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1426 rows containing non-finite values (stat_ydensity).## Warning: Removed 1426 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1346 rows containing non-finite values (stat_ydensity).## Warning: Removed 1346 rows containing non-finite values (stat_boxplot).
5.7.2 Per individual
/sm/
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sm/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 63 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sm/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 50 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sm/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 135 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sm/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 108 rows containing non-finite values (stat_boxplot).
/sp/
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sp/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 88 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sp/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 59 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sp/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 72 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sp/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 45 rows containing non-finite values (stat_boxplot).
/sx/
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sx/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 285 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sx/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 278 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sx/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 273 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sx/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 253 rows containing non-finite values (stat_boxplot).
/spr/
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/spr/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 549 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/spr/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 705 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/spr/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 607 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/spr/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 721 rows containing non-finite values (stat_boxplot).
5.8 Some plots
5.8.1 Per group
/sm/
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, c-center", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 198 rows containing non-finite values (stat_ydensity).## Warning: Removed 198 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, rightedge", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 158 rows containing non-finite values (stat_ydensity).## Warning: Removed 158 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sm/, leftedge", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 563 rows containing non-finite values (stat_ydensity).## Warning: Removed 563 rows containing non-finite values (stat_boxplot).
/sp/
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, c-center", y = "Lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 160 rows containing non-finite values (stat_ydensity).## Warning: Removed 160 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 104 rows containing non-finite values (stat_ydensity).## Warning: Removed 104 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sp/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 516 rows containing non-finite values (stat_ydensity).## Warning: Removed 516 rows containing non-finite values (stat_boxplot).
/sx/
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, c-center", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 558 rows containing non-finite values (stat_ydensity).## Warning: Removed 558 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 531 rows containing non-finite values (stat_ydensity).## Warning: Removed 531 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/sx/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 604 rows containing non-finite values (stat_ydensity).## Warning: Removed 604 rows containing non-finite values (stat_boxplot).
/spr/
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=c.center.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, c-center", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1156 rows containing non-finite values (stat_ydensity).## Warning: Removed 1156 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=rightedge.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, rightedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1426 rows containing non-finite values (stat_ydensity).## Warning: Removed 1426 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr',], aes(x=group, y=leftedge.lag, fill=condition)) + geom_violin() + labs(title = "/spr/, leftedge", y = "lag") + geom_boxplot(width=.2, position = dodge) + ylim(80, 350)## Warning: Removed 1346 rows containing non-finite values (stat_ydensity).## Warning: Removed 1346 rows containing non-finite values (stat_boxplot).
5.8.2 Per individual
/sm/
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sm/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 63 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sm/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 50 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sm/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 135 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sm' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sm/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 108 rows containing non-finite values (stat_boxplot).
/sp/
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sp/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 88 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sp/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 59 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sp/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 72 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sp' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sp/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 45 rows containing non-finite values (stat_boxplot).
/sx/
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sx/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 285 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sx/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 278 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/sx/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 273 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'sx' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/sx/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 253 rows containing non-finite values (stat_boxplot).
/spr/
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'CTRL',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/spr/, c-center, CTRL", y = "lag") + geom_boxplot(width=.5 )+ ylim(80, 350)## Warning: Removed 549 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'CTRL',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/spr/, rightedge, CTRL", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 705 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'PD',], aes(x=subj, y=c.center.lag, fill=condition)) + labs(title = "/spr/, c-center, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 607 rows containing non-finite values (stat_boxplot).
ggplot(df.C.center[df.C.center$cluster == 'spr' & df.C.center$group == 'PD',], aes(x=subj, y=rightedge.lag, fill=condition)) + labs(title = "/spr/, rightedge, PD", y = "lag") + geom_boxplot(width=.5) + ylim(80, 350)## Warning: Removed 721 rows containing non-finite values (stat_boxplot).
5.9 Derive standard deviations
df.RSD <- df.C.center %>%
group_by(subj, cluster) %>%
drop_na(leftedge.lag, rightedge.lag, c.center.lag) %>%
mutate(sd.leftedge = sd(leftedge.lag)) %>%
mutate(mean.dur.leftedge = mean(leftedge.lag)) %>%
mutate(RSD.leftedge = 100*sd.leftedge/mean.dur.leftedge) %>%
mutate(sd.rightedge = sd(rightedge.lag)) %>%
mutate(mean.dur.rightedge = mean(rightedge.lag)) %>%
mutate(RSD.rightedge = 100*sd.rightedge/mean.dur.rightedge) %>%
mutate(sd.C.center = sd(c.center.lag)) %>%
mutate(mean.dur.C.center = mean(c.center.lag)) %>%
mutate(RSD.C.center = 100*sd.C.center/mean.dur.C.center) %>%
distinct(subj, RSD.leftedge, RSD.rightedge, RSD.C.center, .keep_all = T)
ggplot(df.RSD, aes(x=subj, y=RSD.leftedge, fill = group)) + geom_boxplot()
ggplot(df.RSD, aes(x=subj, y=RSD.rightedge, fill = group)) + geom_boxplot()
ggplot(df.RSD, aes(x=subj, y=RSD.C.center, fill = group)) + geom_boxplot()
#transform wide format to long format
df.RSD.long <- df.RSD %>%
group_by(subj, group, cluster) %>%
gather(condition,RSD,c(RSD.leftedge, RSD.rightedge, RSD.C.center)) %>%
select(subj, group, cluster, condition, RSD) %>%
arrange(subj, group, cluster, condition, RSD)
df.RSD.long$subj <- droplevels(df.RSD.long$subj)
df.RSD.long$condition <- as.factor(df.RSD.long$condition)
#ezANOVA(RSD.long, dv=value, wid=subj, within=condition, between=group)
# display group means
df.RSD %>%
group_by(group, cluster) %>%
summarize(mean.leftedge = mean(RSD.leftedge), sd.leftedge = sd(RSD.leftedge), mean.rightedge = mean(RSD.rightedge), sd.rightedge = sd(RSD.rightedge), mean.C.center = mean(RSD.C.center), sd.C.center = sd(RSD.C.center)) %>%
gather(condition,value,c(mean.leftedge, mean.rightedge, mean.C.center))## `summarise()` regrouping output by 'group' (override with `.groups` argument)6 Save data
#add meta_data
setwd("/Users/45598770/Documents/analysis/data")
df_meta <- read.csv("metadata.csv", header = TRUE, sep = ",")
df_meta$gender <- as.factor(df_meta$gender)
df.CC.lag <- merge(df.CC.lag, df_meta, by="subj")
rm(df_meta)
# Set variables that consist of most datapoints as reference variables
df.CC.lag$gender <- relevel(df.CC.lag$gender, ref = "M")
df.CC.lag$group <- relevel(df.CC.lag$group, ref = "CTRL")
df.CC.lag$dialect <- relevel(df.CC.lag$dialect, ref = "Rest")
saveRDS(df.CC.lag, file="modelling_data_CC.rds")
saveRDS(df.RSD.long, file="modelling_data_RSD.rds")